INSIGHTS FROM EXPERTS ON LINKEDIN
Sam Jefferies says many tour operators pour all their budget into chasing the small group of buyers who are ready right now, which drives up costs and competition. He points to the 95-5 rule and a 60/40 style split, arguing that more money should go toward building future demand, not just capturing existing demand. The idea is to stop fighting over the same buyers and start creating more of them over time.
Rob Muldoon shares how his team uses Fibbler to track which companies engage with LinkedIn Ads and turn that data into useful signals for sales. By sending engagement data through webhooks into tools like Clay, Google Sheets, and outreach platforms, they turn ad activity into both direct sales follow-up and automated prospecting. He sees it as a simple, affordable way to connect marketing performance with real pipeline impact.
Liam Moroney argues that growing political tension between the U.S. and Europe could make global marketing tech far more complex. With governments pushing for tech sovereignty and local infrastructure, marketers may soon face stricter rules about where data lives and which tools can be used. He believes this shift will make deep local market knowledge and classic 4P marketing skills more important than ever.
Ben Dutter says the real difference in measurement isn’t B2B vs B2C, it’s low-value vs high-value deals. Enterprise, sales-led motions have long cycles, few conversions, and messy data, which makes classic tools like MMMs and geo tests almost impossible to run well. He suggests focusing on leading indicators, list-based holdouts, pipeline value, and simply asking buyers how they found you, while lower-value, self-serve models can use more traditional B2C-style measurement.
Maja Voje argues that mass cold outreach is dying and that 2026 belongs to signal-based prospecting. She shares a free list of 52 triggers across company changes, news, hiring, and tech stack shifts that can be used to time outreach when intent is highest. The winning combo depends on deep ICP understanding and better data, not copying someone else’s playbook.
Krists Jakabsons highlights a new LinkedIn feature that automatically compares company page metrics across selected time periods. What used to require manual work can now be seen instantly, making reporting and trend spotting much easier. It’s a minor update, but one that opens up quicker insights for page performance.
Philip Ilic explains that when your target list is small and high value, LinkedIn strategy should focus on long-term content exposure, not quick lead capture. The goal is to build familiarity with key stakeholders through consistent mid-funnel content, measured by frequency, account penetration, and engagement. Once recognition is strong, demand capture tactics like outbound and bottom-funnel offers can do their job.
Carilu Dietrich talks about the constant frustration of broken attribution and messy CRM data, where real marketing influence gets lost before big reporting moments. She’s excited about new AI tools that can analyze unstructured data like call recordings, emails, and documents to reconstruct a fuller, more accurate picture of how deals actually happen. The promise is a clearer view of marketing and partner impact without days of manual detective work.
Everett Berry shares his excitement about Clay adding direct ad platform integrations, helping teams build and sync richer audiences to LinkedIn, Meta, and Google. By combining website intent data, contact enrichment, and ad ID matching, marketers can run more precise ABM-style campaigns straight from Clay. Early feedback points to much stronger match rates and new ways to connect paid ads with outbound and messaging workflows.
Angela Sun highlights a Descript ad that clearly spells out who the product competes with and why its all-in-one approach is better, almost like publishing an internal positioning doc. She praises the bold, explicit comparison and how directly it communicates where the product fits. She also raises the question of whether this kind of upfront competitive messaging carries risks, especially from a product marketing perspective.
Ali Yildirim
explains how Clay’s Ads beta dramatically improves audience match rates by sending multiple enriched data fields, not just emails, to ad platforms. This leads to fresher, more accurate audiences that sync automatically and reduce wasted spend from poor matches. Early tests show better CPLs and conversions, while also saving teams time previously spent on manual list uploads.
WHAT'S NEW IN THE INDUSTRY
Meta is experimenting with paid subscription tiers across Instagram, Facebook, and WhatsApp that unlock advanced tools, audience insights, and expanded AI features, while keeping core access free. The move could change how people create and share content, which in turn may affect engagement patterns, organic reach, and the signals advertisers rely on. It’s also a push to diversify revenue beyond ads, but success depends on whether users see enough value to pay monthly.
New data shows U.S. users are doing nearly 20% fewer Google searches per person year over year, suggesting AI-powered answers are reducing the need for repeat queries. While overall search usage is still strong, discovery is getting more concentrated, with traffic flowing to a handful of dominant platforms and fewer clicks going to the wider web. For marketers and publishers, that means fewer chances to capture attention through traditional search and more competition for visibility.
Google Ads introduced a new Experiment Center that brings A/B tests and lift studies into one unified dashboard for easier planning and analysis. Advertisers can now test bidding, targeting, and creative strategies alongside brand and conversion lift studies without jumping between tools. The update makes structured testing more accessible as automation increases and marketers need clearer ways to prove what’s actually driving results.
OpenAI is rolling out ads inside ChatGPT at premium CPMs, offering brands visibility in AI conversations but only basic metrics like impressions and clicks. Advertisers won’t get user-level targeting or conversion data, since OpenAI says it won’t sell user data or compromise chat privacy. Early tests are likely to focus more on brand exposure and learning than on direct performance results.
Google now lets advertisers preview Performance Max images and videos with a single click прямо from the asset group table. The update removes extra steps, making it easier to check how creatives will look across placements while staying in the same workflow. It’s a small usability win that helps teams manage and review large creative libraries more efficiently.
Microsoft reported $81.3 billion in quarterly revenue with cloud revenue topping $50 billion for the first time, driven by strong Azure growth and continued AI investment. Search and news advertising still grew, but at a slower 10% rate, marking a cooldown compared to previous quarters. The company is pouring tens of billions into infrastructure to support AI and cloud demand, signaling long-term bets even as some ad momentum eases.
Google released version 23 of the Ads API, adding deeper Performance Max reporting, more detailed invoicing data, and new AI-driven audience capabilities. Advertisers also get finer scheduling controls and more granular performance insights across Shopping and Demand Gen campaigns. The update reflects Google’s push toward faster product cycles and more automation-focused campaign management.
That’s the scoop for this week! If you found this valuable and any useful insights caught your eye, feel free to share them with your network.
Until next week!
